The Future of IT Operations in the AI Era survey examines AI readiness in manufacturing, with 62% of AI projects in pilot or development stages, and 90% of respondents agree that improving data quality is critical to AI success
Riverbed has released manufacturing sector findings from its global survey, The Future of IT Operations in the AI Era, highlighting strong interest in AI but clear gaps in readiness.
While 87% of manufacturing leaders say their AIOps investments have delivered expected or better ROI, only 37% feel fully prepared to deploy AI at scale. Most AI initiatives (62%) are still in pilot or development stages, and 90% agree that improving data quality is essential for AI success.
The results show manufacturers are eager to use AI to improve operations, cut costs, and manage complex supply chains — but many are still working to turn AI ambitions into large-scale execution
As organizations in the manufacturing sector aim to advance their AI journey, there are several significant barriers hindering wide-scale adoption. While more than half (57%) of manufacturing organizations express confidence in their AI projects, and the vast majority agree that improving data quality is critical to success, persistent data quality challenges remain a central obstacle.
Almost half (47%) lack confidence in the accuracy and completeness of their data to be able to deliver the right outcomes, and only 34% rate their data as excellent for relevance and suitability. These gaps highlight a clear disconnect between leadership optimism and the technical realities of implementation.
“The manufacturing industry is investing heavily in AI to transform IT operations, and our survey results show that nearly nine in ten companies in this sector (87%) are already meeting or exceeding ROI expectations from their AIOps investments,” said Richard Tworek, Chief Technology Officer, at Riverbed. “However, many still face major challenges, including gaps in readiness and preparedness, as well as data quality issues which are hindering progress. As a data-driven company, we’re helping our manufacturing customers close these gaps with safe, secure and accurate AI built on high-quality real data; delivering practical AI-powered solutions that enable organizations to scale AI across the enterprise.”
Tool consolidation a top IT priority for manufacturers
Amid changing processes and varying priorities, manufacturers have pursued an array of IT tools to support shifting goals. The research found that, on average, organizations in this industry currently use 13 observability tools from nine different vendors. In response, 95% of manufacturers are consolidating tools to cut down on sprawl in an effort to reduce costs, streamline operations, and optimize efficiencies across IT operations.
Vendors will be well-served to continue exploring their tools’ capabilities, with 91% of manufacturing organizations considering new tools as they look to consolidate. The top capabilities and drivers manufacturing leaders are actively considering when consolidating tools include enhancing tool integration and interoperability (48%), reducing vendor management overhead (47%), and improving IT productivity (46%).
Unified communication in need of reform
With AI and remote work set to transform manufacturing organizations worldwide, the survey found enthusiasm for unified communication tools and their integration into operations.
- The research revealed that 42% of employees use UC tools throughout their work week and 66% of manufacturing respondents say that these tools are essential to operating effectively on a weekly basis.
- Despite growing adoption, these tools still have significant room for improvement. Less than half (45%) are satisfied with UC tools’ performance, and 42% of manufacturers report experiencing issues with video calls, messaging platforms, and more.
- The top three challenges organizations face with UC tools include limited visibility (51%), dropped calls (42%), and integration challenges with other enterprise systems (38%).
Adoption of OpenTelemetry across manufacturing
Manufacturing leaders surveyed also report their views on OpenTelemetry (OTel) and its place within their organization. The research found that 44% have fully implemented OTel, with a further 42% adopting it, and overall, 97% agree that cross-domain OpenTelemetry correlation is critical to their observability strategy.
The vast majority (93%) say that OTel is a foundation for future initiatives such as AI-driven automation and 37% cite that OTel is already a mandate in their organization, indicating a substantial interest in this technology.
AI data movement and network performance
With data already identified as a key factor to critical success in the implementation of AI initiatives, 91% of manufacturing respondents cited the movement and sharing of data as important to their organization’s overall AI strategy, with 31% stating it’s critical and foundational to how they design and executive AI. To further support AI initiatives, 75% of manufacturing respondents plan to establish an AI data repository strategy by 2028.
Respondents also confirmed their top three considerations when enabling their organization to move and scale data effectively were:
- Network performance and ability (96%)
- Cost of data movement and storage (94%)
- AI model proximity to data, and interoperability between environments (both 93%)
Additionally, as manufacturing organizations strive to stay competitive, ensuring superior network efficiency and robust data security is a top priority, as 79% report that network performance and security are essential to their AI strategy.
